Oracle Machine Learning with Autonomous Database Course Overview

Oracle Machine Learning with Autonomous Database Course Overview

The Oracle Machine Learning with Autonomous Database course is an educational program designed to equip learners with the skills to leverage Oracle Machine Learning (OML) within the Oracle Autonomous Database environment. Throughout the course, participants will explore various components and features of OML, understand how to create and manage workspaces and projects, and how to execute SQL scripts and commands. They'll gain practical knowledge through hands-on experiences with notebooks for data analysis, learn to collaborate using templates, and manage OML jobs.

Learners will navigate the intricacies of administering OML, working with Oracle Machine Learning using Autonomous Transaction Processing Cloud, and creating impactful visualizations using Oracle Analytics Cloud. By the end of the course, attendees will be proficient in oracle machine learning using autonomous database and oracle machine learning with autonomous database, empowering them to perform data analysis, machine learning, and data visualization within the Oracle Cloud ecosystem. This comprehensive course roadmap ensures that participants are well-prepared to harness the power of OML for data-driven decision-making.

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  • Live Online Training (Duration : 16 Hours)
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  • Live Online Training (Duration : 16 Hours)
  • Per Participant

♱ Excluding VAT/GST

Classroom Training price is on request

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Course Prerequisites

To successfully undertake training in the Oracle Machine Learning with Autonomous Database course, students should ideally have the following minimum prerequisites:


  • Basic understanding of database concepts and data management
  • Familiarity with SQL and experience in writing SQL queries
  • An introductory knowledge of machine learning concepts and techniques
  • General awareness of cloud computing and Oracle Cloud services
  • Comfort with using web interfaces for software interaction

Please note that while these prerequisites are aimed at ensuring a smooth learning experience, we encourage students with varying levels of expertise and backgrounds to enroll. Our course is designed to guide learners through the fundamentals before progressing to more advanced topics.


Target Audience for Oracle Machine Learning with Autonomous Database

The Oracle Machine Learning with Autonomous Database course is designed for IT professionals looking to specialize in data analytics and machine learning.


  • Data Scientists and Analysts
  • Database Administrators (DBAs)
  • BI (Business Intelligence) Specialists
  • Data Engineers
  • Machine Learning Engineers
  • Cloud Solutions Architects
  • IT Consultants specializing in Oracle technologies
  • Application Developers with a focus on analytics and data-driven applications
  • IT Managers overseeing data management and analytics teams
  • Professionals aiming for roles involving Oracle Autonomous Database
  • Students and academics in IT fields seeking practical skills in machine learning with Oracle products


Learning Objectives - What you will Learn in this Oracle Machine Learning with Autonomous Database?

Introduction to Learning Outcomes:

This course equips participants with comprehensive skills in leveraging Oracle Machine Learning on the Autonomous Database to analyze data, build models, and create visualizations for actionable insights.

Learning Objectives and Outcomes:

  • Understand the growth and features of Oracle Machine Learning and its integration with Oracle Autonomous Cloud Platform.
  • Create, manage, and set permissions for projects and workspaces within Oracle Machine Learning.
  • Develop, execute, and manage SQL scripts and commands, understanding the restrictions and best practices.
  • Utilize Oracle Machine Learning Notebooks for data analysis, including creating and editing notebooks, and setting up different forms and output formats.
  • Employ collaboration techniques by using and sharing templates and leveraging export options to enhance team efficiency.
  • Schedule and manage jobs within Oracle Machine Learning, along with viewing and interpreting job logs for improved workflow management.
  • Administer Oracle Machine Learning by managing user data, compute resources, and creating user accounts.
  • Execute typical workflows for data analysis and model building using Oracle Machine Learning with Autonomous Transaction Processing.
  • Integrate Oracle Analytics Cloud with Autonomous Data Warehouse and Transaction Processing Clouds to analyze data and create predictive visualizations.
  • Apply machine learning algorithms like K-means and leverage Oracle Analytics Cloud for data curation, analysis, and visualization to drive business decisions.